Big data and learning analytics in higher education : current theory and practice / Ben Kei Daniel, editor.

Format
Book
Language
English
Published/​Created
  • Switzerland : Springer, [2017].
  • ©2017
Description
1 online resource.

Availability

Available Online

Details

Subject(s)
Editor
Summary note
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.
Bibliographic references
Includes bibliographical references index.
Source of description
Online resource, title from PDF title page (viewed on December 13, 2017).
Contents
  • Chapter 1: Overview of Big Data and Analytics in Higher Education
  • Chapter 2: Thoughts on Recent Trends and Future Research Perspectives in Big Data and Analytics in Higher Education
  • Chapter 3: Big Data in Higher Education: The Big Picture
  • Chapter 4: Preparing the Next Generation of Education Researchers for Big Data in Higher Education
  • Chapter 5: Managing the Embedded Digital Ecosystems (EDE) Using Big Data Paradigm
  • Chapter 6: The Contemporary Research University and the Contest for Deliberative Space
  • Part II: LEARNING ANALYTICS
  • Chapter 7: Ethical Considerations in Adopting a University- and System-Wide Approach to Data and Learning Analytics
  • Chapter 8: Big Data, Higher Education and Learning Analytics: Beyond Justice, Towards an Ethics of Care
  • Chapter 9: Curricular and Learning Analytics: A Big Data Perspective
  • Chapter 10: Implementing a Learning Analytics Intervention and Evaluation Framework: What Works?
  • Chapter 11: GraphFES: A Web Service and Application for Moodle Message Board Social Graph Extraction
  • Chapter 12: Toward an Open Learning Analytics Ecosystem
  • Chapter 13: Predicting Four-Year Student Success from Two-Year Student Data
  • Chapter 14: Assessing Science Inquiry Skills in an Immersive, Conversation-Based Scenario
  • Chapter 15: Learning Analytics of Clinical Anatomy e-Cases.
ISBN
  • 9783319065205 ((electronic bk.))
  • 3319065203 ((electronic bk.))
OCLC
957557899
Other standard number
  • 99971908626
Statement on language in description
Princeton University Library aims to describe library materials in a manner that is respectful to the individuals and communities who create, use, and are represented in the collections we manage. Read more...
Other views
Staff view

Supplementary Information