Big Data and Learning Analytics in Higher Education

Current Theory and Practice

  • Ben Kei Daniel

Table of contents

  1. Front Matter
    Pages i-xx
  2. BIG DATA

  3. LEARNING ANALYTICS

    1. Front Matter
      Pages 87-87
    2. Colin Pinnell, Geetha Paulmani, Vivekanandan Kumar, Kinshuk
      Pages 125-145
    3. Bart Rienties, Simon Cross, Zdenek Zdrahal
      Pages 147-166
    4. Ángel Hernández-García, Ignacio Suárez-Navas
      Pages 167-194
    5. Mohamed Amine Chatti, Arham Muslim, Ulrik Schroeder
      Pages 195-219
    6. Denise Nadasen, Alexandra List
      Pages 221-236
    7. Diego Zapata-Rivera, Lei Liu, Lei Chen, Jiangang Hao, Alina A. von Davier
      Pages 237-252
    8. Vivek Perumal, Ben Daniel, Russell Butson
      Pages 253-263
  4. Back Matter
    Pages 265-272

About this book

Introduction

This book focuses on the uses of big data in the context of higher education. The book describes a wide range of administrative and operational data gathering processes aimed at assessing institutional performance and progress in order to predict future performance, and identifies potential issues related to academic programming, research, teaching and learning​.  Big data refers to data which is fundamentally too big and complex and moves too fast for the processing capacity of conventional database systems.  The value of big data is the ability to identify useful data and turn it into useable information by identifying patterns and deviations from patterns​.

Keywords

Data on Students, Teaching, Learning, and Research Data-Driven Decision Making Database Technologies Improving the Quality and Value of Higher Learning Patterns in Educational Technology Technology in Higher Education

Editors and affiliations

  • Ben Kei Daniel
    • 1
  1. 1.University of OtagoDunedinNew Zealand

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-06520-5
  • Copyright Information Springer International Publishing Switzerland 2017
  • Publisher Name Springer, Cham
  • eBook Packages Education
  • Print ISBN 978-3-319-06519-9
  • Online ISBN 978-3-319-06520-5
  • About this book