Big Data and Learning Analytics in Higher Education

1. Front Matter

   Pages i-xx

   PDF

2. Overview of Big Data and Analytics in Higher Education

   • Ben Kei Daniel

   Pages 1-4

3. BIG DATA

   1. Front Matter

      Pages 5-5

      PDF

   2. Thoughts on Recent Trends and Future Research Perspectives in Big Data and Analytics in Higher Education

      • Jay Liebowitz

      Pages 7-17

   3. Big Data in Higher Education: The Big Picture

      • Ben K. Daniel

      Pages 19-28

   4. Preparing the Next Generation of Education Researchers for Big Data in Higher Education

      • David C. Gibson, Dirk Ifenthaler

      Pages 29-42

   5. Managing the Embedded Digital Ecosystems (EDE) Using Big Data Paradigm

      • Shastri L. Nimmagadda, Amit Rudra

      Pages 43-72

   6. The Contemporary Research University and the Contest for Deliberative Space

      • Tony Harland

      Pages 73-86

4. LEARNING ANALYTICS

   1. Front Matter

      Pages 87-87

      PDF

   2. Ethical Considerations in Adopting a University- and System-Wide Approach to Data and Learning Analytics

      • Lynne D. Roberts, Vanessa Chang, David Gibson

      Pages 89-108

   3. Big Data, Higher Education and Learning Analytics: Beyond Justice, Towards an Ethics of Care

      • Paul Prinsloo, Sharon Slade

      Pages 109-124

   4. Curricular and Learning Analytics: A Big Data Perspective

      • Colin Pinnell, Geetha Paulmani, Vivekanandan Kumar, Kinshuk

      Pages 125-145

   5. Implementing a Learning Analytics Intervention and Evaluation Framework: What Works?

      • Bart Rienties, Simon Cross, Zdenek Zdrahal

      Pages 147-166

   6. GraphFES: A Web Service and Application for Moodle Message Board Social Graph Extraction

      • Ángel Hernández-García, Ignacio Suárez-Navas

      Pages 167-194

   7. Toward an Open Learning Analytics Ecosystem

      • Mohamed Amine Chatti, Arham Muslim, Ulrik Schroeder

      Pages 195-219

   8. Predicting Four-Year Student Success from Two-Year Student Data

      • Denise Nadasen, Alexandra List

      Pages 221-236

   9. Assessing Science Inquiry Skills in an Immersive, Conversation-Based Scenario

      • Diego Zapata-Rivera, Lei Liu, Lei Chen, Jiangang Hao, Alina A. von Davier

      Pages 237-252

   10. Learning Analytics of Clinical Anatomy e-Cases

       • Vivek Perumal, Ben Daniel, Russell Butson

       Pages 253-263

5. Back Matter

   Pages 265-272

   PDF

​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​.

• 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
• learning and instruction

• University of Otago, Dunedin, New Zealand

  Ben Kei Daniel

Dr Ben Daniel is a Senior Lecturer in Higher Education, and heads the Educational Technology Group at the University of Otago—New Zealand. In 2007 he completed his Ph.D. jointly in Computer Science and Educational Technology at the University of Saskatchewan in Canada. 

Previously, Dr Daniel was a Lecturer and a Senior Health Research and Innovation Analyst with the Office of Associate Vice President Research-Health (University of Saskatchewan)/Vice President Research and Innovation (Saskatoon Health Region)—Saskatoon, Canada. For over a decade Dr Daniel taught undergraduate, postgraduate students, academic staff, and Senior Corporate Executives on Research Methodologies; Program Evaluation and Logic Modelling; Quality Improvement, Statistics and Biostatistics as well as Advanced Learning Technologies. 

An active researcher, Dr Daniel has published over 50 peer-reviewed publications (2 edited books, 2 authored book, 13 book chapters, 10 peer-reviewed journal articles, 26 peer-reviewed conference papers, 10 peer-reviewed workshops and posters, and over 10 technical reports).  His current research is focused generally on exploring the value of Big Data and learning analytics in influencing learning, teaching and research in the context of higher education. He is also investigating theories and praxis of teaching research methodologies in Higher Education and the corporate sector.

 

Policies and ethics